The cortical energy needed for conscious perception

Paying the brain's energy bill

How have animals managed to maintain metabolically expensive brains given the volatile and fleeting availability of calories in the natural world? Here we review studies in support of three strategies that involve: 1) a reallocation of energy from peripheral tissues and functions to cover the costs of the brain, 2) an implementation of energy-efficient neural coding, enabling the brain to operate at reduced energy costs, and 3) efficient use of costly neural resources during food scarcity. Collectively, these studies reveal a heterogeneous set of energy-saving mechanisms that make energy-costly brains fit for survival.

Energy supply per neuron is constrained by capillary density in the mouse brain

Neuronal densities vary enormously across sites within a brain. Does the density of the capillary bed vary accompanying the presumably larger energy requirement of sites with more neurons, or with larger neurons, or is energy supply constrained by a mostly homogeneous capillary bed? Here we find evidence for the latter, with a capillary bed that represents typically between 0.7 and 1.5% of the volume of the parenchyma across various sites in the mouse brain, whereas neuronal densities vary by at least 100-fold. As a result, the ratio of capillary cells per neuron decreases uniformly with increasing neuronal density and therefore with smaller average neuronal size across sites. Thus, given the relatively constant capillary density compared to neuronal density in the brain, blood and energy availability per neuron is presumably dependent on how many neurons compete for the limited supply provided by a mostly homogeneous capillary bed. Additionally, we find that local capillary density is not correlated with local synapse densities, although there is a small but significant correlation between lower neuronal density (and therefore larger neuronal size) and more synapses per neuron within the restricted range of 6,500–9,500 across cortical sites. Further, local variations in the glial/neuron ratio are not correlated with local variations in the number of synapses per neuron or local synaptic densities. These findings suggest that it is not that larger neurons, neurons with more synapses, or even sites with more synapses demand more energy, but simply that larger neurons (in low density sites) have more energy available per cell and for the totality of its synapses than smaller neurons (in high density sites) due to competition for limited resources supplied by a capillary bed of fairly homogeneous density throughout the brain.

The thermodynamics of thinking: connections between neural activity, energy metabolism and blood flow

Several current functional neuroimaging methods are sensitive to cerebral metabolism and cerebral blood flow (CBF) rather than the underlying neural activity itself. Empirically, the connections between metabolism, flow and neural activity are complex and somewhat counterintuitive: CBF and glycolysis increase more than seems to be needed to provide oxygen and pyruvate for oxidative metabolism, and the oxygen extraction fraction is relatively low in the brain and decreases when oxygen metabolism increases. This work lays a foundation for the idea that this unexpected pattern of physiological changes is consistent with basic thermodynamic considerations related to metabolism. In the context of this thermodynamic framework, the apparent mismatches in metabolic rates and CBF are related to preserving the entropy change of oxidative metabolism, specifically the O₂/CO₂ ratio in the mitochondria. However, the mechanism supporting this CBF response is likely not owing to feedback from a hypothetical O₂ sensor in tissue, but rather is consistent with feed-forward control by signals from both excitatory and inhibitory neural activity. Quantitative predictions of the thermodynamic framework, based on models of O₂ and CO₂ transport and possible neural drivers of CBF control, are in good agreement with a wide range of experimental data, including responses to neural activation, hypercapnia, hypoxia and high-altitude acclimatization. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.

How many neurons are sufficient for perception of cortical activity?

Many theories of brain function propose that activity in sparse subsets of neurons underlies perception and action. To place a lower bound on the amount of neural activity that can be perceived, we used an all-optical approach to drive behaviour with targeted two-photon optogenetic activation of small ensembles of L2/3 pyramidal neurons in mouse barrel cortex while simultaneously recording local network activity with two-photon calcium imaging. By precisely titrating the number of neurons stimulated, we demonstrate that the lower bound for perception of cortical activity is ~14 pyramidal neurons. We find a steep sigmoidal relationship between the number of activated neurons and behaviour, saturating at only ~37 neurons, and show this relationship can shift with learning. Furthermore, activation of ensembles is balanced by inhibition of neighbouring neurons. This surprising perceptual sensitivity in the face of potent network suppression supports the sparse coding hypothesis, and suggests that cortical perception balances a trade-off between minimizing the impact of noise while efficiently detecting relevant signals.

Central Nervous System Correlates of "Objective" Neuropathy in Alcohol Use Disorder

BACKGROUND

Among the neurological consequences of alcoholism is peripheral neuropathy. Relative to human immunodeficiency virus (HIV) or diabetes-related neuropathies, neuropathy associated with alcohol use disorders (AUD) is understudied. In both the diabetes and HIV literature, emerging evidence supports a central nervous system (CNS) component to peripheral neuropathy.

METHODS

In seeking a central substrate for AUD-related neuropathy, the current study was conducted in 154 individuals with AUD (43 women, age 21 to 74 years) and 99 healthy controls (41 women, age 21 to 77 years) and explored subjective symptoms (self-report) and objective signs (perception of vibration, deep tendon ankle reflex, position sense, 2-point discrimination) of neuropathy separately. In addition to regional brain volumes, risk factors for AUD-related neuropathy, including age, sex, total lifetime ethanol consumed, nutritional indices (i.e., thiamine, folate), and measures of liver integrity (i.e., γ-glutamyltransferase), were evaluated.

RESULTS

The AUD group described more subjective symptoms of neuropathy and was more frequently impaired on bilateral perception of vibration. From 5 correlates, the number of AUD-related seizures was most significantly associated with subjective symptoms of neuropathy. There were 15 correlates of impaired perception of vibration among the AUD participants: Of these, age and volume of frontal precentral cortex were the most robust predictors.

CONCLUSIONS

This study supports CNS involvement in objective signs of neuropathy in AUD.

Consciousness as a Physical Process Caused by the Organization of Energy in the Brain

To explain consciousness as a physical process we must acknowledge the role of energy in the brain. Energetic activity is fundamental to all physical processes and causally drives biological behavior. Recent neuroscientific evidence can be interpreted in a way that suggests consciousness is a product of the organization of energetic activity in the brain. The nature of energy itself, though, remains largely mysterious, and we do not fully understand how it contributes to brain function or consciousness. According to the principle outlined here, energy, along with forces and work, can be described as actualized differences of motion and tension. By observing physical systems, we can infer there is something it is like to undergo actualized difference from the intrinsic perspective of the system. Consciousness occurs because there is something it is like, intrinsically, to undergo a certain organization of actualized differences in the brain.

Interpreting BOLD: towards a dialogue between cognitive and cellular neuroscience

Cognitive neuroscience depends on the use of blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to probe brain function. Although commonly used as a surrogate measure of neuronal activity, BOLD signals actually reflect changes in brain blood oxygenation. Understanding the mechanisms linking neuronal activity to vascular perfusion is, therefore, critical in interpreting BOLD. Advances in cellular neuroscience demonstrating differences in this neurovascular relationship in different brain regions, conditions or pathologies are often not accounted for when interpreting BOLD. Meanwhile, within cognitive neuroscience, the increasing use of high magnetic field strengths and the development of model-based tasks and analyses have broadened the capability of BOLD signals to inform us about the underlying neuronal activity, but these methods are less well understood by cellular neuroscientists. In 2016, a Royal Society Theo Murphy Meeting brought scientists from the two communities together to discuss these issues. Here, we consolidate the main conclusions arising from that meeting. We discuss areas of consensus about what BOLD fMRI can tell us about underlying neuronal activity, and how advanced modelling techniques have improved our ability to use and interpret BOLD. We also highlight areas of controversy in understanding BOLD and suggest research directions required to resolve these issues.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

Neurovascular-neuroenergetic coupling axis in the brain: master regulation by nitric oxide and consequences in aging and neurodegeneration

The strict energetic demands of the brain require that nutrient supply and usage be fine-tuned in accordance with the specific temporal and spatial patterns of ever-changing levels of neuronal activity. This is achieved by adjusting local cerebral blood flow (CBF) as a function of activity level - neurovascular coupling - and by changing how energy substrates are metabolized and shuttled amongst astrocytes and neurons - neuroenergetic coupling. Both activity-dependent increase of CBF and O₂ and glucose utilization by active neural cells are inextricably linked, establishing a functional metabolic axis in the brain, the neurovascular-neuroenergetic coupling axis. This axis incorporates and links previously independent processes that need to be coordinated in the normal brain. We here review evidence supporting the role of neuronal-derived nitric oxide (^•NO) as the master regulator of this axis. Nitric oxide is produced in tight association with glutamatergic activation and, diffusing several cell diameters, may interact with different molecular targets within each cell type. Hemeproteins such as soluble guanylate cyclase, cytochrome c oxidase and hemoglobin, with which ^•NO reacts at relatively fast rates, are but a few of the key in determinants of the regulatory role of ^•NO in the neurovascular-neuroenergetic coupling axis. Accordingly, critical literature supporting this concept is discussed. Moreover, in view of the controversy regarding the regulation of catabolism of different neural cells, we further discuss key aspects of the pathways through which ^•NO specifically up-regulates glycolysis in astrocytes, supporting lactate shuttling to neurons for oxidative breakdown. From a biomedical viewpoint, derailment of neurovascular-neuroenergetic axis is precociously linked to aberrant brain aging, cognitive impairment and neurodegeneration. Thus, we summarize current knowledge of how both neurovascular and neuroenergetic coupling are compromised in aging, traumatic brain injury, epilepsy and age-associated neurodegenerative disorders such as Alzheimer's disease and Parkinson's disease, suggesting that a shift in cellular redox balance may contribute to divert ^•NO bioactivity from regulation to dysfunction.

Deconvolution of neural dynamics from fMRI data using a spatiotemporal hemodynamic response function

Functional magnetic resonance imaging (fMRI) is a powerful and broadly used means of non-invasively mapping human brain activity. However fMRI is an indirect measure that rests upon a mapping from neuronal activity to the blood oxygen level dependent (BOLD) signal via hemodynamic effects. The quality of estimated neuronal activity hinges on the validity of the hemodynamic model employed. Recent work has demonstrated that the hemodynamic response has non-separable spatiotemporal dynamics, a key property that is not implemented in existing fMRI analysis frameworks. Here both simulated and empirical data are used to demonstrate that using a physiologically based model of the spatiotemporal hemodynamic response function (stHRF) results in a quantitative improvement of the estimated neuronal response relative to unphysical space-time separable forms. To achieve this, an integrated spatial and temporal deconvolution is established using a recently developed stHRF. Simulated data allows the variation of key parameters such as noise and the spatial complexity of the neuronal drive, while knowing the neuronal input. The results demonstrate that the use of a spatiotemporally integrated HRF can avoid "ghost" neuronal responses that can otherwise be falsely inferred. Applying the spatiotemporal deconvolution to high resolution fMRI data allows the recovery of neuronal responses that are consistent with independent electrophysiological measures.

The contribution of electrophysiology to functional connectivity mapping

A powerful way to probe brain function is to assess the relationship between simultaneous changes in activity across different parts of the brain. In recent years, the temporal activity correlation between brain areas has frequently been taken as a measure of their functional connections. Evaluating 'functional connectivity' in this way is particularly popular in the fMRI community, but has also drawn interest among electrophysiologists. Like hemodynamic fluctuations observed with fMRI, electrophysiological signals display significant temporal fluctuations, even in the absence of a stimulus. These neural fluctuations exhibit a correlational structure over a wide range of spatial and temporal scales. Initial evidence suggests that certain aspects of this correlational structure bear a high correspondence to so-called functional networks defined using fMRI. The growing family of methods to study activity covariation, combined with the diverse neural mechanisms that contribute to the spontaneous fluctuations, has somewhat blurred the operational concept of functional connectivity. What is clear is that spontaneous activity is a conspicuous, energy-consuming feature of the brain. Given its prominence and its practical applications for the functional connectivity mapping of brain networks, it is of increasing importance that we understand its neural origins as well as its contribution to normal brain function.

Preserving neural function under extreme scaling

Important brain functions need to be conserved throughout organisms of extremely varying sizes. Here we study the scaling properties of an essential component of computation in the brain: the single neuron. We compare morphology and signal propagation of a uniquely identifiable interneuron, the HS cell, in the blowfly (Calliphora) with its exact counterpart in the fruit fly (Drosophila) which is about four times smaller in each dimension. Anatomical features of the HS cell scale isometrically and minimise wiring costs but, by themselves, do not scale to preserve the electrotonic behaviour. However, the membrane properties are set to conserve dendritic as well as axonal delays and attenuation as well as dendritic integration of visual information. In conclusion, the electrotonic structure of a neuron, the HS cell in this case, is surprisingly stable over a wide range of morphological scales.

Synaptic energy use and supply

Neuronal computation is energetically expensive. Consequently, the brain's limited energy supply imposes constraints on its information processing capability. Most brain energy is used on synaptic transmission, making it important to understand how energy is provided to and used by synapses. We describe how information transmission through presynaptic terminals and postsynaptic spines is related to their energy consumption, assess which mechanisms normally ensure an adequate supply of ATP to these structures, consider the influence of synaptic plasticity and changing brain state on synaptic energy use, and explain how disruption of the energy supply to synapses leads to neuropathology.

A variational approach to behavioral and neuroelectrical laws

Variational methods play a fundamental and unifying role in several fields of physics, chemistry, engineering, economics, and biology, as they allow one to derive the behavior of a system as a consequence of an optimality principle. A possible application of these methods to a model of perception is given by considering a psychophysical law as the solution of an Euler-Lagrange equation. A general class of Lagrangians is identified by requiring the measurability of prothetic continua on interval scales. The associated Hamiltonian (the energy of the process) is tentatively connected with neurophysiological aspects. As an example of the suggested approach a particular choice of the Lagrangian, that is a sufficient condition to obtain classical psychophysical laws, while accounting for psychophysical adaptation and the stationarity of neuronal activity, is used to explore a possible relation between a behavioral law and a neuroelectrical ,response based on the Naka-Rushton model.

Altered anesthetic sensitivity of mice lacking Ndufs4, a subunit of mitochondrial complex I

Anesthetics are in routine use, yet the mechanisms underlying their function are incompletely understood. Studies in vitro demonstrate that both GABA(A) and NMDA receptors are modulated by anesthetics, but whole animal models have not supported the role of these receptors as sole effectors of general anesthesia. Findings in C. elegans and in children reveal that defects in mitochondrial complex I can cause hypersensitivity to volatile anesthetics. Here, we tested a knockout (KO) mouse with reduced complex I function due to inactivation of the Ndufs4 gene, which encodes one of the subunits of complex I. We tested these KO mice with two volatile and two non-volatile anesthetics. KO and wild-type (WT) mice were anesthetized with isoflurane, halothane, propofol or ketamine at post-natal (PN) days 23 to 27, and tested for loss of response to tail clamp (isoflurane and halothane) or loss of righting reflex (propofol and ketamine). KO mice were 2.5 - to 3-fold more sensitive to isoflurane and halothane than WT mice. KO mice were 2-fold more sensitive to propofol but resistant to ketamine. These changes in anesthetic sensitivity are the largest recorded in a mammal.

The physiology of developmental changes in BOLD functional imaging signals

BOLD fMRI (blood oxygenation level dependent functional magnetic resonance imaging) is increasingly used to detect developmental changes of human brain function that are hypothesized to underlie the maturation of cognitive processes. BOLD signals depend on neuronal activity increasing cerebral blood flow, and are reduced by neural oxygen consumption. Thus, developmental changes of BOLD signals may not reflect altered information processing if there are concomitant changes in neurovascular coupling (the mechanism by which neuronal activity increases blood flow) or neural energy use (and hence oxygen consumption). We review how BOLD signals are generated, and explain the signalling pathways which convert neuronal activity into increased blood flow. We then summarize in broad terms the developmental changes that the brain's neural circuitry undergoes during growth from childhood through adolescence to adulthood, and present the changes in neurovascular coupling mechanisms and energy use which occur over the same period. This information provides a framework for assessing whether the BOLD changes observed during human development reflect altered cognitive processing or changes in neurovascular coupling and energy use.

Glial and neuronal control of brain blood flow

Blood flow in the brain is regulated by neurons and astrocytes. Knowledge of how these cells control blood flow is crucial for understanding how neural computation is powered, for interpreting functional imaging scans of brains, and for developing treatments for neurological disorders. It is now recognized that neurotransmitter-mediated signalling has a key role in regulating cerebral blood flow, that much of this control is mediated by astrocytes, that oxygen modulates blood flow regulation, and that blood flow may be controlled by capillaries as well as by arterioles. These conceptual shifts in our understanding of cerebral blood flow control have important implications for the development of new therapeutic approaches.